About HqO
HqO is connecting real estate to the people with an asset agnostic, cross-property suite of powerful applications and services that foster best-in-class, dynamic end-user experiences. HqO’s REX (Real Estate Experience) Platform assesses the health and performance of a person’s experience within a physical space while providing the necessary tools for operators to manage and optimize it, all from one central location.
HqO has been trusted to power 400 million+ square feet across 700+ properties in 32 countries, and we’re backed by some of the world’s most prominent VC and real estate companies as we continue to grow rapidly across the world.
We’re driven by our core values of LET’S GO (Learning, Excellence, Truth, Service, Goodness, Ownership) which define our culture and push us to do our best work every day. If you want to join a fast-growing, highly collaborative, and supportive team that is at the forefront of real estate transformation, we’re the company for you.
Please see the bottom of this application for more details on how to apply!
About the Role
HqO is leading the transformation of the way people experience real estate by converging data, technology, and the customer. Empowering data-driven strategies and real estate decisions, we're redefining the way people experience space, and in turn, helping to create vibrant, engaging communities.Our REX Platform is used by leading commercial real estate owners and occupiers to activate their spaces, engage tenants, and measure what matters. We are a 100-person company that moves fast, operates with high ownership, and takes AI seriously and a culture that rewards builders.
We're hiring our first Applied AI Engineer: someone who will embed directly with our Operations and DevOps teams to identify high-leverage problems, build production-grade AI agents and automations, and ship tools that make the company measurably more effective.
We care less about where you trained and more about what you've built. We look for slope over intercept. If you have high agency, move with urgency, and get energized by turning ambiguous problems into working systems — read on.
How You'll Make an Impact
Identify and own high-leverage problems
Build and ship AI-powered systems
Drive adoption and measure impact
Raise the AI ceiling across the company
What We're Looking For
We're open to a variety of backgrounds. The signal we care most about is your ability to build and ship real things with AI.
Non-negotiables
Strong signals
Who you are
Why This Role Matters
At HqO's scale, one highly capable Applied AI Engineer can materially change how the entire company operates. You won't be one of many — you'll be the person who builds the internal AI layer for a company with real customers, real stakes, and ambitious growth goals.
You'll have direct access to leadership, latitude to define your own roadmap, and a foundation of 15+ production agents already deployed to build on. The problems are real, the systems are in use, and the impact is visible. This isn't a proof-of-concept role.
We're a company in an industry — commercial real estate — being fundamentally transformed by AI. The person in this role will help define how that transformation happens from the inside.
How to Apply
Submit your application with the following:
Applications reviewed on a rolling basis. Finalists will be invited to a Builder Day at HqO's Boston office on July 29th. Date subject to change
Applied AI Engineer Application - Due July 16th
README & Video Submission Template
Complete all required sections. Optional sections noted. Your video and README will be evaluated using the rubric at the end of this document.
All Application Questions & Requirements in the Questionnaire Section on the following page
Evaluation Rubric
Projects are scored out of 100 points across four categories.
Category | Points | What Evaluators Look For |
Problem Framing & Real-World Impact | 0–25 | Good: Interesting problem with a defined audience. Candidate explains the pain point and why they chose to build it. Great: Specific, well-scoped problem tied to a meaningful workflow. Shows product thinking: who is affected, what success looks like, why AI was the right tool, and how to quantify impact. |
Technical Execution | 0–35 | Good: Functional solution with readable code. README covers setup. Shows end-to-end build capability. Great: Clean, well-structured code with clear architecture decisions. Reproducible. Demonstrates thoughtful design: modularity, error handling, sensible tradeoffs. Setup instructions work out of the box. |
AI Fluency: Building with AI & Using AI | 0–25 | Good: LLM/AI tools are central to the solution. Candidate describes how coding tools accelerated development with some reflection. Great: Agentic patterns, RAG, tool use, or non-trivial orchestration. Candidate articulates how AI coding tools changed their process, where they hit limits, and how they adapted. Shows AI as a force multiplier at both the product and dev levels. |
Communication & Documentation | 0–15 | Good: Video walkthrough is clear and covers core functionality. README explains solution, architecture, and setup. Great: Video explains not just "what" but "why." README includes architecture decisions, tradeoffs, and future improvements. Candidate can speak to technical decisions for a non-technical audience. |
Tiebreaker: Builder Mindset | N/A | Did the candidate go beyond the prompt? Is there evidence of curiosity and iteration, honest reflection on what didn't work, or creative problem framing? Does this person seem like someone who would move with urgency and take initiative from day one without being asked? |
PD
Boston, MA
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